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A regional registration technique for automated interval change analysis of breast lesions on mammograms
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Analysis of interval change is a useful technique for detection of abnormalities in mammographic interpretation. Interval change analysis is routinely used by radiologists and its importance is well‐established in clinical practice. As a first step to develop a computerized method for interval change analysis on mammograms, we are developing an automated regional registration technique to identify corresponding lesions on temporal pairs of mammograms. In this technique, the breast is first segmented from the background on the current and previous mammograms. The breast edges are then aligned using a global alignment procedure based on the mutual information between the breast regions in the two images. Using the nipple location and the breast centroid estimated independently on both mammograms, a polar coordinate system is defined for each image. The polar coordinate of the centroid of a lesion detected on the most recent mammogram is used to obtain an initial estimate of its location on the previous mammogram and to define a fan‐shaped search region. A search for a matching structure to the lesion is then performed in the fan‐shaped region on the previous mammogram to obtain a final estimate of its location. In this study, a quantitative evaluation of registration accuracy has been performed with a data set of 74 temporal pairs of mammograms and ground‐truth correspondence information provided by an experienced radiologist. The most recent mammogram of each temporal pair exhibited a biopsy‐proven mass. We have investigated the usefulness of correlation and mutual information as search criteria for determining corresponding regions on mammograms for the biopsy‐proven masses. In 85% of the cases (63/74 temporal pairs) the region on the previous mammogram that corresponded to the mass on the current mammogram was correctly identified. The region centroid identified by the registration technique had an average distance of 2.8±1.9 mm from the centroid of the radiologist‐identified region. These results indicate that our new registration technique may be useful for establishing correspondence between structures on current and previous mammograms. Once such a correspondence is established an interval change analysis could be performed to aid in both detection as well as classification of abnormal breast densities.
Title: A regional registration technique for automated interval change analysis of breast lesions on mammograms
Description:
Analysis of interval change is a useful technique for detection of abnormalities in mammographic interpretation.
Interval change analysis is routinely used by radiologists and its importance is well‐established in clinical practice.
As a first step to develop a computerized method for interval change analysis on mammograms, we are developing an automated regional registration technique to identify corresponding lesions on temporal pairs of mammograms.
In this technique, the breast is first segmented from the background on the current and previous mammograms.
The breast edges are then aligned using a global alignment procedure based on the mutual information between the breast regions in the two images.
Using the nipple location and the breast centroid estimated independently on both mammograms, a polar coordinate system is defined for each image.
The polar coordinate of the centroid of a lesion detected on the most recent mammogram is used to obtain an initial estimate of its location on the previous mammogram and to define a fan‐shaped search region.
A search for a matching structure to the lesion is then performed in the fan‐shaped region on the previous mammogram to obtain a final estimate of its location.
In this study, a quantitative evaluation of registration accuracy has been performed with a data set of 74 temporal pairs of mammograms and ground‐truth correspondence information provided by an experienced radiologist.
The most recent mammogram of each temporal pair exhibited a biopsy‐proven mass.
We have investigated the usefulness of correlation and mutual information as search criteria for determining corresponding regions on mammograms for the biopsy‐proven masses.
In 85% of the cases (63/74 temporal pairs) the region on the previous mammogram that corresponded to the mass on the current mammogram was correctly identified.
The region centroid identified by the registration technique had an average distance of 2.
8±1.
9 mm from the centroid of the radiologist‐identified region.
These results indicate that our new registration technique may be useful for establishing correspondence between structures on current and previous mammograms.
Once such a correspondence is established an interval change analysis could be performed to aid in both detection as well as classification of abnormal breast densities.
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